The partitioning of large data sets into similar subsets (Cluster Analysis) is an important statistical technique used in many fields (data mining, machine learning, bioinformatics, and pattern recognition and image analysis). In traffic research, it is useful both to determine and to recognize the types of vehicles passing a checkpoint. Traffic data collection systems would collect data (e.g., vehicle length, distances between axles, weights on. axles) and such data may be used to determine and recognize vehicle types in high volume traffic, monitoring traffic volumes of various types of vehicles forecasting future road maintenance costs and planning and design of future road networks.
The consequence of such determination and recognition of vehicle types in high volume traffic has many applications, e g, monitoring traffic volumes of various types of vehicles, forecasting future road maintenance costs and planning and design of future road networks.